Vibration Data Neural network signal analysis, with some signal processing modification, has been employed in the art to identify and to diagnose problems in machinery and in products being manufactured.
As an example, in U.S. Pat. No. 5,361,628 diagnostic testing and classification of automobile engines is described, in which, in connection with a neural network, subsampling and filtration for reduction of a vibration signal band is used in order not to overload the neural network.
In general, heretofore in the art problem identification and diagnostic systems involving a neural network are set up and optimized under static conditions using known parameters. There are however, conditions that may evolve in operation, such as changes in the material being processed, changes in one or more of the sensed parameters such as rotation rate, and progressive changes such as the increasing effect of bearing deterioration, that can cause an overall system to perform less than optimally with an attendant reduction in accuracy and responsiveness.